Pickl AI

MAY 29, 2024

Machine Learning Algorithms Understanding and implementing Machine Learning Algorithms is a core requirement. Knowledge of supervised and unsupervised learning and techniques like clustering, classification, and regression is essential. This skill allows the creation of predictive models and insights from data.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 23, 2024

AI, particularly Machine Learning and Deep Learning uses these insights to develop intelligent models that can predict outcomes, automate processes, and adapt to new information. Deep Learning: Advanced neural networks drive Deep Learning , allowing AI to process vast amounts of data and recognise complex patterns.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Pickl AI

JULY 25, 2023

Model Development Data Scientists develop sophisticated machine-learning models to derive valuable insights and predictions from the data. These models may include regression, classification, clustering, and more. Statistical Analysis: Hypothesis testing, probability, regression analysis, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 12, 2024

Boosting: An ensemble learning technique that combines multiple weak models to create a strong predictive model. C Classification: A supervised Machine Learning task that assigns data points to predefined categories or classes based on their characteristics.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

There are majorly two categories of sampling techniques based on the usage of statistics, they are: Probability Sampling techniques: Clustered sampling, Simple random sampling, and Stratified sampling. What is deep learning? What is the difference between deep learning and machine learning?

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. Are there any areas in data analytics where you want to improve or learn more? You’re tasked with predicting sales for a retail store. What approach would you take?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Data Science Dojo

AUGUST 30, 2023

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. Hypothesis testing, correlation, and regression analysis, and distribution analysis are some of the essential statistical tools that data scientists use.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195